1. Field of the Invention
The present invention relates to an apparatus for removing the Partial Discharge (PD) noise of a power facility and an apparatus for detecting a PD occurrence section, which can promptly remove noise from a PD signal generated by a power facility such as a Gas Insulated Switchgear (GIS), and can detect a PD occurrence section.
2. Description of the Related Art
Generally, in most domestic power plants/substations, Gas Insulated Switchgears (GISs) are used. Such a GIS is an integrated switch device in which disconnectors, buses, ground devices, transformers, etc. are accommodated in a metal box and in which a charging unit is insulated using an SF6 gas, that is, a single system into which disconnectors, arrestors, circuit breakers, etc., which were separately provided in existing substations, are integrated. Such a GIS is not only safer than a previous open-type switch device due to its insulation performance, but also has a greatly reduced insulation area. Therefore, in most current substations, GISs have been newly established or existing switch devices have been replaced with GISs. Therefore, it is required to ensure maintenance management technology and permanent insulation diagnosis technology which guarantee reliability so as to prevent accidents related to GISs and stably operate GISs.
Korean Patent Appln. No. 2007-60191 entitled “Method and apparatus for analyzing the cause of partial discharge of a GIS using a Phase Resolved Pulse Sequence (PRPS) algorithm,” filed by the applicant of the present invention (hereinafter referred to as “prior art”), describes permanent insulation diagnosis technologies for conventional GISs designed to meet such requirements.
The prior art is configured to include a sensor unit, an analog processing unit, an Analog/Digital (A/D) converter, a digital signal processing unit, a database (DB) unit for storing the reference characteristic patterns of a neural network algorithm, a neutral network circuit, a second neural network circuit, and a final probability calculation unit. The prior art amplifies the analog signals of electromagnetic waves generated from the inside of a GIS, detects the maximum value of the analog signals, converts the maximum value into a digital signal, divides each voltage phase cycle appearing for a preset analysis unit time by a predetermined value into binaries which are unitary intervals, ands calculates an input vector composed of the sum of the numbers of discharges of in-phase binaries placed in the cycle of each voltage phase and the average discharge signal intensity of the in-phase binaries discharge signals, which is obtained by dividing the sum of the numbers of discharges by the number of cycles. Further, the prior art calculates a probability that the input vectors calculated by the neural network circuit and the second neural network circuit will be identical to each individual reference characteristic pattern of the DB unit by assigning different weights to the input vectors, applies weights calculated from recognition rates for respective causes of PD to the probabilities for the respective causes of the PD, which are output from the neural network circuit and the second neural network circuit, adds the resulting probabilities for respective PD causes, and calculates a single probability, so that noise or the like which is the cause of the PD can be analyzed, thus enabling PD occurring inside the GIS to be analyzed for respective causes.
In this case, in the above-described prior art, a sensor is shielded or, alternatively, a band pass filter used in hardware is employed so that noise is prevented from flowing into a portion around the sensor so as to remove the noise when a PD signal is measured.
However, a noise removal method applied to the above-described prior art can efficiently remove noise in the case when normal noise is to be removed, but cannot remove noise attributable to a nearby motor or wideband impulse noise occurring in a welding machine or the like. Further, in the case of a band pass filter, when a noise frequency band is included in the pass band thereof, noise is input as a signal required to analyze the patterns of PD without being removed, and thus a problem arises in that a resulting value output from a probability calculation unit is erroneously calculated to cause noise to be erroneously determined and to be a PD signal.
Accordingly, the present invention has been made keeping in mind the above problems occurring in the prior art, and an object of the present invention is to provide an apparatus for removing the PD noise of a power facility and an apparatus for detecting a PD occurrence section, which can precisely and easily remove a noise signal, measured by a noise sensor, from radio wave signals detected by a measurement sensor provided inside a GIS, thus detecting a PD occurrence section while remarkably improving the reliability of resulting values obtained by PD pattern analysis devices such as conventional PRPS devices.